Dynamic range is the ratio between the largest and smallest possible signals a sensor or an actuator can generate. As used herein, the term “dynamic range” refers to the dynamic range of an image capture device, such as a digital camera.
To capture HDR images of a scene, multiple frames of this scene are generally captured by a HDR image capture device under varying exposures. In a traditional setup of this device, the exposures are generally spaced such as to cover the full distribution of illumination in the scene. Such a process is known as “exposure bracketing”. Modern cameras allow the capture of 3 to 9 exposure brackets, which may be spaced ⅓ f-stop to 3 f-stops apart, where 1 f-stop is one logarithmic unit. F-stop is the ratio of the focal length of the camera lens to the diameter of the entrance pupil of this lens. To create an HDR image from these frames having different exposures, the sequence of exposures is merged by combining in a manner known per se the well exposed parts of each exposure. In general, exposures are scaled according to their exposure time and each pixel of each frame receives a weight factor depending on its light intensity—pixels closer to the middle of the range receive higher weight as they are more likely to depict useful information. See for instance: Pradeep Sen, Nima Khademi Kalantari, Maziar Yaesoubi, Soheil Darabi, Dan B. Goldman, and Eli Shechtman. Robust patch-based HDR reconstruction of dynamic scenes. ACM Transactions on Graphics, 31(6): 203:1-203:11, 2012.
Typically, exposures of the different frames used to build an HDR image are evenly spaced. Because of the even spacing of the exposures, these solutions have a number of weaknesses. First, too many exposures may be captured, each replicating a lot of the content of adjacent exposures. Second, if exposures are spaced further away, the resulting HDR image may suffer from too much noise in dark areas.
In the article entitled “Metering for exposure stacks”, published in 2012 by Orazio Gallo et al. in Computer Graphics Forum, volume 31, pages 479-488 (Wiley Online Library), before capturing the set of exposures used to build an HDR image, an algorithm estimates the HDR histogram of the scene using low resolution exposures. Based on this histogram, all combinations of exposures are tested to decide which is optimal for the scene to HDR capture. To guide the selection and placement of exposures, noise characteristics are also taken into account so that the final selection minimizes noise. Then the series of exposures is captured with these settings. Since this approach is designed for capturing a single HDR image it has the following disadvantages:
No motion is considered;
It is not practical for video as it requires the full HDR histogram to be built. This would cause too many lost frames and therefore the final result would be low frame rate.
The same conclusions apply to the document U.S. Pat. No. 7,382,931 and U.S. Pat. No. 8,582,001.
When applying such a HDR process to video capture, alternating frames are captured successively using different exposure settings: such a process is called “temporal bracketing”. But, as some objects in the scene may move during the capture of the successive exposures used to build each HDR image of the video (or the camera may move) and as these different exposures capture the scene at different times, the merging of these exposures may create motion artefacts. Moreover, as the frequency of HDR images is a division of the frame frequency allowed by the video image capture device, this HDR frequency may be too low to avoid motion blurring.
Therefore, there is a need for a tradeoff between high dynamic range and sharp motion capture.